AskNow: A Framework for Natural Language Query Formalization in SPARQL

  • Mohnish Dubey
  • Sourish Dasgupta
  • Ankit Sharma
  • Konrad Höffner
  • Jens Lehmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9678)

Abstract

Natural Language Query Formalization involves semantically parsing queries in natural language and translating them into their corresponding formal representations. It is a key component for developing question-answering (QA) systems on RDF data. The chosen formal representation language in this case is often SPARQL. In this paper, we propose a framework, called AskNow, where users can pose queries in English to a target RDF knowledge base (e.g. DBpedia), which are first normalized into an intermediary canonical syntactic form, called Normalized Query Structure (NQS), and then translated into SPARQL queries. NQS facilitates the identification of the desire (or expected output information) and the user-provided input information, and establishing their mutual semantic relationship. At the same time, it is sufficiently adaptive to query paraphrasing. We have empirically evaluated the framework with respect to the syntactic robustness of NQS and semantic accuracy of the SPARQL translator on standard benchmark datasets.

References

  1. 1.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, pp. 697–706. ACM (2007)Google Scholar
  3. 3.
    Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 1247–1250. ACM (2008)Google Scholar
  4. 4.
    Dong, X., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., Murphy, K., Strohmann, T., Sun, S., Zhang, W.: Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 601–610. ACM (2014)Google Scholar
  5. 5.
    Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of SPARQL. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 30–43. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Lopez, V., Unger, C., Cimiano, P., Motta, E.: Evaluating question answering over linked data. Web Semant. Sci. Serv. Agents World Wide Web 21, 3–13 (2013)CrossRefGoogle Scholar
  7. 7.
    Mendes, P.N., Jakob, M., García-Silva, A., Bizer, C.: Dbpedia spotlight: shedding light on the web of documents. In: Proceedings of the 7th International Conference on Semantic Systems, pp. 1–8. ACM (2011)Google Scholar
  8. 8.
    Miller, G.A.: Wordnet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  9. 9.
    Gerber, D., Ngonga Ngomo, A.-C.: Bootstrapping the linked data web. In: 1st Workshop on Web Scale Knowledge Extraction @ ISWC (2011)Google Scholar
  10. 10.
    Unger, C., Forascu, C., Lopez, V., Ngomo, A.-C.N., Cabrio, E., Cimiano, P., Walter, S.: Question answering over linked data (QALD-5). In: Working Notes for CLEF Conference (2015)Google Scholar
  11. 11.
    Unger, C., Forascu, C., Lopez, V., Ngomo, A.-C.N., Cabrio, E., Cimiano, P., Walter, S.: Question answering over linked data (QALD-4). In: Working Notes for CLEF Conference (2014)Google Scholar
  12. 12.
    Bernstein, A., Kaufmann, E., Kaiser, C.: Querying the semantic web with ginseng: a guided input natural language search engine. In: 15th Workshop on Information Technologies and Systems, Las Vegas, NV, pp. 112–126. Citeseer (2005)Google Scholar
  13. 13.
    Kaufmann, E., Bernstein, A.: How useful are natural language interfaces to the semantic web for casual end-users? In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 281–294. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. 14.
    Lopez, V., Uren, V., Motta, E., Pasin, M.: Aqualog: an ontology-driven question answering system for organizational semantic intranets. Web Semant. Sci. Serv. Agents World Wide Web 5(2), 72–105 (2007)CrossRefGoogle Scholar
  15. 15.
    Lopez, V., Fernández, M., Motta, E., Stieler, N.: Poweraqua: supporting users in querying and exploring the semantic web. Semant. Web 3(3), 249–265 (2012)Google Scholar
  16. 16.
    Damljanovic, D., Agatonovic, M., Cunningham, H.: FREyA: an interactive way of querying linked data using natural language. In: García-Castro, R., Fensel, D., Antoniou, G. (eds.) ESWC 2011. LNCS, vol. 7117, pp. 125–138. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Kaufmann, E., Bernstein, A., Fischer, L.: NLP-reduce: a naıve but domain-independent natural language interface for querying ontologies. In: ESWC, Zurich (2007)Google Scholar
  18. 18.
    Lehmann, J., Bühmann, L.: AutoSPARQL: let users query your knowledge base. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 63–79. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  19. 19.
    Unger, C., Bühmann, L., Lehmann, J., Ngonga Ngomo, A.-C, Gerber, D., Cimiano, P.: Template-based question answering over RDF data. In: Proceedings of the 21st International Conference on World Wide Web, pp. 639–648. ACM (2012)Google Scholar
  20. 20.
    Cimiano, P., Lopez, V., Unger, C., Cabrio, E., Ngonga Ngomo, A.-C., Walter, S.: Multilingual question answering over linked data (QALD-3): lab overview. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 321–332. Springer, Heidelberg (2013)Google Scholar
  21. 21.
    Ferré, S.: squall2sparql: a translator from controlled English to full SPARQL 1.1. In: Working Notes of Multilingual Question Answering over Linked Data (QALD-3) (2013)Google Scholar
  22. 22.
    Marginean, A.: GFMed: question answering over biomedical linked data with grammatical framework. In: CLEF (2014)Google Scholar
  23. 23.
    Ranta, A.: Grammatical Framework: Programming with Multilingual Grammars. CSLI Publications, Stanford (2011)Google Scholar
  24. 24.
    Hamon, T., Grabar, N., Mougin, F., Thiessard, F.: Description of the pomelo system for the task 2 of QALD-2014. In: CLEF (2014)Google Scholar
  25. 25.
    Zou, L., Huang, R., Wang, H., Yu, J.X., He, W., Zhao, D.: Natural language question answering over RDF: a graph data driven approach. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 313–324. ACM (2014)Google Scholar
  26. 26.
    Xu, K., Zhang, S., Feng, Y., Zhao, D.: Answering natural language questions via phrasal semantic parsing. In: Zong, C., Nie, J.-Y., Zhao, D., Feng, Y. (eds.) NLPCC 2014. CCIS, vol. 496, pp. 333–344. Springer, Heidelberg (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mohnish Dubey
    • 1
  • Sourish Dasgupta
    • 2
  • Ankit Sharma
    • 3
  • Konrad Höffner
    • 4
  • Jens Lehmann
    • 1
    • 5
  1. 1.Computer Science InstituteUniversity of BonnBonnGermany
  2. 2.DA-IICTGandhinagarIndia
  3. 3.State University of New YorkBuffaloUSA
  4. 4.AKSW GroupUniversity of LeipzigLeipzigGermany
  5. 5.Fraunhofer IAISSankt AugustinGermany

Personalised recommendations